Human beings use various channels and media to obtain information. Among sense organs of a human body, the eye plays the most important role as an entrance for perceiving and receiving information. According to statistics, it is known that about 70% of the perceived and received information is obtained through a sense of vision among the human senses (vision, hearing, smell, taste and touch).
In the past, the perceived and received information was generally transmitted through a medium of letter. However, with a rapid development of computers and transmission media, image information by an image media holds the most important part as an object and subject in information communications of a modern society.
As information communication techniques develop in an aspect of hardware, various techniques also develop to transmit image information more rapidly and effectively. And, many methods are disclosed to satisfy various objects of image processing.
The image processing includes feature extraction, image enhancement, image restoration, image reconstruction, image analysis, image recognition and image compression. In particular, in recent days, the image processing has a main interest in a method for reducing noise that may occur during image compression and processing involved in transmission of image information or during transmission of image information.
Various methods were introduced to reduce noise according to purpose and utility, however conventionally noise reduction was performed only in consideration of simple average or deviation of pixels adjacent to an object pixel for noise reduction.
The conventional method considers a uniform and statistical methodology without reflecting a correlation or relationship between pixels. This results in a simple and easy calculation process, but vulnerability against loss of main characteristics (hue, location, edge and so on) of an image.
And, the conventional method uniformly uses simple average value and location information of adjacent pixels, and as a result, incidental errors may continuously occur during a calculation process and further noise may occur even after application of an algorithm.
Synthetically judging, in most cases, the conventional method does not consider information of a pixel of an image, such as brightness, hue, edge or location when reducing noise or a false color of the image, and thus has a disadvantage of loss of the above-mentioned information.
Further, in the case that a digital image is generated using various contemporary digital cameras and mobile phones on the market, various erroneous information may occur to image information, for example noise occurring in setting a high ISO (International Standards Organization) value to increase sensitivity in a dark environment, noise caused by excessive compression or noise occurring due to dust of a lens or sensor (CMOS (Complementary Metal Oxide Semiconductor) or CCD (Charged Coupled Device)). Therefore, it requires to reduce noise and minimize the loss of a unique information of an image.
In a modern society, an image device is increasingly implemented in a portable and small-sized equipment rather than in an advanced equipment. A conversion device based on a complicated frequency has limitations in image processing due to the restricted size and speed of hardware. Therefore, it needs a method that requires a small-sized hardware resource to apply an embedded system or a chip to an image processing apparatus integrated into a portable terminal and can overcome the above-mentioned problems.